This paper addresses three major issues associated with conventional partitional clustering, namely, sensitivity to initialization, difficulty in determining the number of clusters, and sensitivity to noise and outliers. The proposed Robust Competitive Agglomeration (RCA) algorithm starts with a large number of clusters to reduce the sensitivity to initialization, and determines the actual numb...

This thesis describes a clustering approach to automatically inferring soft semantic classes and characterizing senses of a set of Norwegian nouns. The words are represented by way of their distribution in text, identified as local contexts in the form of lexical-syntactic relations. Through a shallow processing step the context features are extracted for lemmatized word forms in syntactically ...

Identification of the navigational patterns of casual visitors is an important step in online recommendation to convert casual visitors to customers in e-commerce. Clustering and sequential analysis are two primary techniques for mining navigational patterns from Web and application server logs. The characteristics of the log data and mining tasks require new data representation methods and ana...

For hierarchical clustering, dendrograms provide convenient and powerful visualization. Although many visualization methods have been suggested for partitional clustering, their usefulness deteriorates quickly with increasing dimensionality of the data and/or they fail to represent structure between and within clusters simultaneously. In this paper we extend (dissimilarity) matrix shading with ...

Hierarchical clustering is one of the most suitable tools to discover underlying true structure a dataset in case unsupervised learning where ground truth unknown and classical machine classifiers are not suitable. In many real applications, it provides perspective on inner data preferred partitional methods. However, determining resulting number clusters hierarchical requires human expertise d...

The key advantage of smart meters over rotating-disc is their ability to transmit electric energy consumption data power utilities’ remote centers. Besides enabling the automated collection consumers’ for billing purposes, gathered by and analyzed through Artificial Intelligence (AI) make realization consumer-centric use cases possible. A meter installed in a domestic sector an electrical grid ...

Let E be a possibly infinite set and let M N matroids defined on E. We say that the pair {M,N} has Intersection property if share an independent I admitting bipartition IM⊔IN such spanM(IM)∪spanN(IN)=E. The Matroid Conjecture of Nash-Williams says every matroid property. conjecture is known easy to prove in case when one uniform it was shown by Bowler Carmesin implied its special where direct s...

This work applies cluster analysis as a unified approach for a wide range of vision applications, thereby combining the research domain of computer vision and that of machine learning. Cluster analysis is the formal study of algorithms and methods for recovering the inherent structure within a given dataset. Many problems of computer vision have precisely this goal, namely to find which visual ...

Digital classification methods of remotely sensed images have acquired a growing importance in the automatic recognition of the land cover patterns. The enormous quantity of images that are being generated from an increasing number of highly sophisticated sensor systems require the development of innovative classification methodologies, which allow an automatic and efficient detection of the gr...

We claim ̄rst that simple uncertainty is not an adequate model of a subject's ignorance, because a major component of it is the inability to give a complete description of the states of the world, and we provide a formal model of unawareness. In Modica and Rustichini (1994) we showed a di±culty in the project, namely that without weakening of the inference rules of the logic one would face the ...